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The serious wear problem of heavy-haul freight vehicle wheels affects the safety and economy of vehicle operation. This paper aims to study wheel wear evolution law and the influence of line parameters on wheel wear of heavy-haul freight, and provide the basis for operation and line maintenance.

The wheel wear test data of heavy-haul freight vehicles were analyzed. Then a heavy-haul freight vehicle dynamic model was established. The line parameters influencing wheel wear in heavy-haul freight vehicles were also analyzed by the Jendel wear model, and the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear were analyzed.

A rail cant of 1:40 results in less wheel wear; an increase in the rail gauge can reduce wheel wear; and when matched with the CHN60 rail, the wear depth is relatively small. A decrease of 9.21% in wheel wear depth when matched with the CHN60 rail profile. The ramp of the heavy-haul line is necessary to consider for calculating wheel wear. When the ramp is considered, the wear depth increases by 8.47%. The larger the ramp, the greater the braking force and therefore, the greater of the wheel wear.

This paper first summarizes the wear characteristics of wheels in heavy-haul freight vehicles and then systematically analyzes the effect of line parameters on wheel wear. In particular, this study researched the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0038/

In order to develop high-strength, high-toughness and high-wear-resistance rails suitable for the development and application of heavy-haul railways.

Based on the trial production of 60 kg·m⁻¹ bainite rails, the Zeiss inverted optical microscope, transmission electron microscope and static hydraulic universal tester were used to test the microstructure and property of rail base metal and welded joints. Meanwhile, a trial laying of rails, wing rails of frogs and switch rails for turnouts was performed to systematically analyze their strength, toughness and wear resistance.

The results show that the base metal of 60 kg·m⁻¹ bainite rail is of a uniform microstructure, with a carbide-free bainite matrix, a few of stable residual austenite and M/A islands, and it features high hardness, good wear resistance and good strength-toughness balance. The welded joint is of a uniform microstructure and has good properties.

A bainite rail, laid in a curve section of heavy-haul railway is able to serve for 48 months with a gross traffic tonnage of nearly 600 million tons, whose service life is more than one time longer than that of pearlite rail; the service life of the wing rail of frog and the switch rail for turnout with 60 kg·m⁻¹ bainite rails is 3–4 times longer than that with U75V rails, and no serious damage occurs. The bainite rails also have strong peeling and spalling resistance.

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

The purpose of this paper is twofold: first, to empirically evaluate the key impediments to the competitiveness of the rail sector in Australia; and second, to provide relevant transport management and policy recommendations for enhanced competitiveness.

This paper has adopted an empirical approach. A survey was developed and distributed among rail stakeholders in Australia. Accordingly, exploratory factor analysis and confirmatory factor analysis were conducted to evaluate the key impeding areas.

This paper found four areas that are impeding rail development, these being infrastructure management, shortage of freight data and poor information sharing, service delivery and organisational and commercial interactions.

The theoretical approach of this thesis can be applied to any freight market where competition exists between different transport modes. However, the specific strategies provided in this research in terms of transportation management, infrastructure planning and policy were made according to the specific market condition, infrastructure quality and regulation that exist in Australia.

The findings provide important implications for both industry and government in terms of making transport planning and policy decisions, but also useful insights by identifying the weak parts of the rail sector and directions to target them.

The notion of the rail stakeholder does not appear to have been previously defined in the literature. Therefore, this research takes a broader view of rail stakeholders to include various interest groups within the rail sector and its operational environment.

Public transit is an essential service for people without access to an automobile, particularly those who are low income, elderly, or with disabilities. Previous research has found that large urban transit agencies receive less state funding per ride provided than suburban agencies. The paper aims to discuss this issue.

Using data from the National Transit Database for 37 of the largest US transit agencies, the authors create a panel data set of services provided and sources of operating funds for the period 1991-2009. The authors develop an equity index that represents the difference between the share of state funding that an agency receives and the share of the total transit rides in the state that it provides. The authors use fixed-effects regression modeling to examine the determinants of fiscal balance and the equity index.

The authors find that the share of an agency’s operating funds that come from dedicated taxes is a significant predictor of fiscal health as measured by its fiscal balance; reliance on passenger fares and provision of bus service are significant predictors of operating deficits. The equity index finds that large agencies receive less than their fair share of state transit funding based on ridership.

Dedicated tax revenues are a key ingredient to transit agencies’ fiscal stability. Transit agencies’ fiscal condition in states and localities that do not have a dedicated tax could benefit from such a tax.

Transit is an essential service for people who are unable to drive or own an automobile; funding inequities maintain old patterns of segregation and isolation for “transit dependents.”

This study supports earlier research finding that large agencies receive less than their fair share of state funding based on ridership. It contributes to the literature on transportation equity and transit finance.